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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA jurnal teknik informatika dan sistem informasi
Laurentius Kuncoro Probo Saputra, Laurentius Kuncoro Probo
Universitas Kristen Duta Wacana
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Sistem Kendali Terpusat Penjadwalan Perangkat Air Conditioner Berbasis Internet of Things Setiawan, Daniel Felix; Saputra, Laurentius Kuncoro Probo; Lukito, Yuan
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 2 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i2.3448

Abstract

Air Conditioner (AC) devices in Duta Wacana Christian University 2nd floor Agape computer laboratory are turned on in the morning and turned off in the evening manually by the computer laboratory officer every day after all the classes are over. Whereas there are sessions when laboratory rooms are not used, but the AC is still on. So, there is a waste of electricity. It wastes time and energy in vain. Therefore, the implementation of AC control and scheduling can be the solution. The implementation includes a program for PC that is used to control the AC and IR module that is attached to the computer laboratory’s AC. IR module consists of NodeMCU ESP8266 microcontroller and IR LED. All microcontrollers are connected to the internet over a WiFi network. The microcontroller substitutes conventional remote control. From the result, it can be concluded that the AC control and scheduling system is successfully implemented and worked well with good performance. After the system is implemented, computer laboratory officers no longer need to turn on and off the AC manually every day. Therefore, it can save energy and time. Besides that, waste of electrical energy can be minimized, because AC will turn off automatically when the laboratory room is not used.
Pengembangan Sistem Pemantauan Aktivitas Pengawasan Satpam dengan Proses Validasi Dinamis QR-Code pada Aplikasi Patrolee Saputra, Laurentius Kuncoro Probo; Raharjo, Willy Sudiarto; Restyandito, Restyandito
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3368

Abstract

Internet of Things (IoT) technology provides system integration to accelerate wireless remote data acquisition. This paper presents the implementation of IoT based applications to monitor security guard surveillance activities in the campus environment. The traditional reporting system still has many limitations. The security guard should make a written report to his supervisor and send the surveillance images using a third-party instant messaging application. The reporting results are not integrated. Implementation of IoT system which consists of Dynamic QR-code Display, Android Application, Web Application, and Cloud Database, enables the integration and real-time reporting system. Security guard reports can be seen directly, both written reports and the surveillance image, using a web application. Each security guard on duty has its unique QR code for each location and current surveillance schedule. It makes the security guard cannot ask their duties to other people. The results of this research show that this system has been able to meet the needs of security officers. The success rate of security guards when doing the task using this application is 90%.
Perbandingan Varian Metode Multiscale Retinex untuk Peningkatan Akurasi Deteksi Wajah Adaboost HAAR-like Saputra, Laurentius Kuncoro Probo
Jurnal Teknik Informatika dan Sistem Informasi Vol 2 No 1 (2016): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v2i1.611

Abstract

Face detection is a popular research in image processing field. Face detection can be used in many application like multi-face recognition, video surveillance, human counter or monitoring. The famous face detection method is developed by Viola-Jones that is named Adaboost using HAAR-like feature. In many research about face detection using Adaboost HAAR-like, it is shown Adaboost HAAR-like face detection method have a limitation in low illumination. In this paper, we want to compare an improvement for increasing accuracy of face detection result using MSRCR and AMSR method. MSRCR and AMSR is an image enhancement method. Finally the results show that MSRCR is better than AMSR for increasing accuracy of face detection result. MSRCR can improve the accuracy until 1,43 times, but AMSR can only improve the accuracy until 1,11 times.
Pemanfaatan Raspberry Pi untuk Sistem Penghitung Mobil Otomatis pada Kampus UKDW Nugraha, Kristian Adi; Saputra, Laurentius Kuncoro Probo
Jurnal Teknik Informatika dan Sistem Informasi Vol 3 No 3 (2017): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v3i3.694

Abstract

The number of vehicle keep increasing over time, causing some problems such as traffic jam and requirement of extra parking space. Universitas Kristen Duta Wacana (UKDW) is an university that has similar problem, lack of parking space at certain hours. That won't be a problem if campus activities such as course, student activities, etc. can spread evenly at all hours, not focused at one time only. But determine the accurate schedule is a difficult task, because it requires someone who observes all vehicles entering and exiting campus area all over time. This research propose a solution to create automatic system that can count all vehicles (car) that entering and exiting campus area, then the data can be used as a consideration in determining the scheduling at the next time, the lack of parking space area can be avoided. The system was built with internet of things technology using Raspberry Pi and camera as the main component with main server at the backend to store the data. That system is also using background substraction algorithm for counting  the number of vehicles that entering and exiting campus area. The accuracy of the system at counting vehicles is 70%.
Co-Authors Kristian Adi Nugraha Restyandito Sebastian, Danny Setiawan, Daniel Felix Willy Sudiarto Raharjo Yuan Lukito